Sub-pocket-focused designing of tacrine derivatives as potential acetylcholinesterase inhibitors

Multi-target potential of newly designed tacrine-derived cholinesterase inhibitors: Synthesis, computational and pharmacological study

Simple and scalable synthetic approach was used for the preparation of thirteen novel tacrine derivatives consisting of tacrine and N-aryl-piperidine-4-carboxamide moiety connected by a five-methylene group linker. An anti-Alzheimer disease (AD) potential of newly designed tacrine derivatives was evaluated against two important AD targets, acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE). In vitro pharmacological evaluation showed strong ChE inhibitory activity of all compounds, with IC50 values ranging from 117.5 to 455 nM for AChE and 34 to 324 nM for BuChE. As a representative of the series with the best cytotoxicity / ChE inhibitory activity ratio, expressed as the selectivity index (SI), 2-chlorobenzoyl derivative demonstrated mixed-type inhibition on AChE and BuChE, suggesting binding to both CAS and PAS of the enzymes. It also exhibited antioxidant capacity and neuroprotective potential against amyloid-β (Aβ) toxicity in the culture of neuron-like cells. In-depth computational analysis corroborated well with in vitro ChE inhibition, illuminating that all compounds exhibit significant potential in targeting both enzymes. Molecular dynamics (MD) simulations revealed that 2-chlorobenzoyl derivative, created complexes with AChE and BuChE that demonstrated sufficient stability throughout the observed MD simulation. Computationally predicted ADME properties indicated that these compounds should have good blood-brain barrier (BBB) permeability, an important factor for CNS-targeting drugs. Overall, all tested compounds showed promising pharmacological behavior, highlighting the multi-target potential of 2-chlorobenzoyl derivative which should be further investigated as a new lead in the drug development process.

Noncovalent binding of carbofuran to acetylcholinesterase from Homo sapiens, Danio rerio, Apis mellifera and Caenorhabditis elegans: Homology modelling, molecular docking and dynamics, and quantum biochemistry description

Although various regulatory agencies have banned or severely restricted the use of carbofuran (CAR), recent reports indicate the presence of CAR residues in both cultivated and wild areas. This pesticide is a potent inhibitor of acetylcholinesterase (AChE), which acts by preventing the hydrolysis of acetylcholine (ACh). Given the critical role of AChE::ACh in the proper functioning of the nervous system, we thought it appropriate to investigate the binding of CAR to AChEs from Homo sapiens, Danio rerio, Apis mellifera, and Caenorhabditis elegans using homology modelling, molecular docking, molecular dynamics, and quantum biochemistry. Molecular docking and dynamics results indicated peculiar structural behavior in each AChE::CAR system. Quantum biochemistry results showed similar affinities for all complexes, confirming the description of carbofuran as a broad-spectrum pesticide, and have a limited correlation with IC50 values. We found the following decreasing affinity order of AChE species: H. sapiens > A. mellifera > C. elegans > D. rerio. The computational results suggest that CAR occupies different pockets in the AChEs studied. In addition, our results showed that CAR binds to hsAChE and ceAChE in a very similar manner: it has high affinities for the same subsites in both species and forms hydrogen bonds with residues (hsTYR124 and ceTRP107) occupying homologous positions in the peripheral site. This suggests that this nematode is a potential model to evaluate the toxicity of carbamates, even though the sequence identity between them is only 41 %. Interestingly, we also observed that the catalytic histidines of drAChE and amAChE exhibited favorable contacts with carbofuran, suggesting that the non-covalent binding of carbofuran to these proteins may promote faster carbamylation rates than the binding modes to human and worm acetylcholinesterases. Our computational results provide a better understanding of the binding mechanisms in these complexes, as well as new insights into the mechanism of carbamylation.